{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T13:20:18Z","timestamp":1740144018825,"version":"3.37.3"},"reference-count":18,"publisher":"Ubiquity Press, Ltd.","license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018,10,3]]},"DOI":"10.5334\/dsj-2018-024","type":"journal-article","created":{"date-parts":[[2018,10,3]],"date-time":"2018-10-03T15:24:07Z","timestamp":1538580247000},"source":"Crossref","is-referenced-by-count":4,"title":["Resembling Population Density Distribution with Massive Mobile Phone Data"],"prefix":"10.5334","volume":"17","author":[{"given":"Teerayut","family":"Horanont","sequence":"first","affiliation":[]},{"given":"Thananut","family":"Phiboonbanakit","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5716-9363","authenticated-orcid":false,"given":"Santi","family":"Phithakkitnukoon","sequence":"additional","affiliation":[]}],"member":"3285","reference":[{"year":"2000","key":"key20181003112220_B1","article-title":"\u2018A random graph model for massive graphs\u2019"},{"key":"key20181003112220_B2","unstructured":"Blondel, VD, et al. 2012. \u2018Data for Development: the D4D Challenge on Mobile Phone Data\u2019. arXiv:1210.0137, 1\u201310. Available at: http:\/\/arxiv.org\/abs\/1210.0137."},{"journal-title":"EPJ Data Science","article-title":"\u2018A survey of results on mobile phone datasets analysis\u2019","year":"2015","key":"key20181003112220_B3"},{"issue":"9","key":"key20181003112220_B4","article-title":"\u2018Inferring Passenger Travel Demand to Improve Urban Mobility in Developing Countries Using Cell Phone Data: A Case Study of Senegal\u2019","volume":"17","year":"2016","journal-title":"IEEE Transactions on Intelligent Transportation Systems"},{"journal-title":"\u2026 Intelligence for Development","article-title":"\u2018A Gender-Centric Analysis of Calling Behavior in a Developing Economy Using Call Detail Records.\u2019","year":"2010","key":"key20181003112220_B5"},{"journal-title":"EPJ Data Science","article-title":"\u2018Improving official statistics in emerging markets using machine learning and mobile phone data\u2019","year":"2017","key":"key20181003112220_B6"},{"year":"2010","key":"key20181003112220_B7","article-title":"\u2018Towards rich mobile phone datasets: Lausanne data collection campaign\u2019"},{"year":"2012","key":"key20181003112220_B8","article-title":"\u2018The mobile data challenge: Big data for mobile computing research\u2019"},{"journal-title":"Physical Review E \u2013 Statistical, Nonlinear, and Soft Matter Physics","article-title":"\u2018Dynamical strength of social ties in information spreading\u2019","year":"2011","key":"key20181003112220_B9"},{"journal-title":"arXiv","article-title":"\u2018D4D-Senegal: The Second Mobile Phone Data for Development Challenge\u2019","year":"2014","key":"key20181003112220_B10"},{"journal-title":"EPJ Data Science","article-title":"\u2018Temporal patterns behind the strength of persistent ties\u2019","year":"2017","key":"key20181003112220_B11"},{"issue":"18","key":"key20181003112220_B12","first-page":"7332","article-title":"\u2018Structure and tie strengths in mobile communication networks\u2019","volume":"104","year":"2006","journal-title":"Proceedings of the National Academy of Sciences (PNAS)"},{"issue":"1","key":"key20181003112220_B13","article-title":"\u2018Inferring social influence in transport mode choice using mobile phone data\u2019","volume":"6","year":"2017","journal-title":"EPJ Data Science"},{"issue":"1","key":"key20181003112220_B14","article-title":"\u2018Mobile social group sizes and scaling ratio\u2019","volume":"26","year":"2011","journal-title":"AI and Society"},{"issue":"6","key":"key20181003112220_B15","article-title":"\u2018Socio-geography of human mobility: A study using longitudinal mobile phone data\u2019","volume":"7","year":"2012","journal-title":"PLoS ONE"},{"journal-title":"European Physical Journal B","article-title":"\u2018From seconds to months: an overview of multi-scale dynamics of mobile telephone calls\u2019","year":"2015","key":"key20181003112220_B16"},{"journal-title":"Science","article-title":"\u2018Limits of predictability in human mobility\u2019","year":"2010","key":"key20181003112220_B17"},{"journal-title":"Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)","article-title":"\u2018Surprising patterns for the call duration distribution of mobile phone users\u2019","year":"2010","key":"key20181003112220_B18"}],"container-title":["Data Science Journal"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/doi.org\/10.5334\/dsj-2018-024","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,7,11]],"date-time":"2022-07-11T09:19:43Z","timestamp":1657531183000},"score":1,"resource":{"primary":{"URL":"http:\/\/datascience.codata.org\/articles\/10.5334\/dsj-2018-024\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"references-count":18,"alternative-id":["10.5334\/dsj-2018-024"],"URL":"https:\/\/doi.org\/10.5334\/dsj-2018-024","relation":{},"ISSN":["1683-1470"],"issn-type":[{"type":"electronic","value":"1683-1470"}],"subject":[],"published":{"date-parts":[[2018]]}}}